It is generally considered to be common knowledge in the art so-called signal processing that if signals are mixed with noise, the S/N ratio becomes worse and the original signals become difficult to obtain. However, creatures in the natural world are living while processing signals mixed with much noise at very low power consumption. The phenomenon called “stochastic resonance” has been found as one of important mechanisms of such signal processing. The stochastic resonance phenomenon is that in a noise-given bistable system there are some cases where the S/N ratio is improved contrary to expectation.
One conventional art attempting to apply such a phenomenon to the industries (hereinafter will be referred to as “first conventional art”) is “METHOD AND APPARATUS FOR DETECTING A SPATIO-TEMPORAL PATTERN, AND RECORDING MEDIUM” described in Japanese Patent Laid-Open Publication No. 2000-3350 for example.
FIG. 13 illustrates a method of detecting detected signals according to the first conventional art. The method described in the first conventional art is to detect signals mixed with noise using an operation method called neural network.
According to the method illustrated in FIG. 13, first of all, the neural network learns a noise-free pattern at steps 101 and 102; thereafter, a noise-mixed signal is inputted to the neural network at step 103; further, stochastic resonance is caused to occur at step 104; and, thereafter, Fourier transformation is performed to find a characteristic frequency peak at step 106, thereby finding the frequency of the original signal from the noise-mixed signal.
The detection method of the first conventional art, however, does not disclose any definition of what in the world the “noise” is. For example, when noise contains an intensive frequency component, this component is undesirably analyzed at the final frequency peak detection step, thus resulting in a problem of inaccurate detection.
Meanwhile, with the recent widespread use of personal computers (PCs), semiconductor devices also find home use significantly widely and hence find increasing personal uses not only for simple numerical operations but also for Internet, mail, image processing and the like.
However, PCs, which have become capable of such high-speed processing, cannot perform all operations at sufficient speed. For example, such processing as to recognize human voices or languages or identify a person on camera requires an enormous amount of operations. For this reason, realtime processing is difficult.
Such recognition processing is based on processing including: vectorizing stored information on voices or faces for example into reference vectors to be stored; likewise, vectorizing inputted information into an inputted vector; detecting similarities between the inputted vector and each of the reference vectors; and performing an operation to find which of the reference vectors is most proximate to the inputted vector. Such vector comparison processing is fundamental processing that can be utilized in a wide variety of information processing including associative storage, quantization of vectors, pattern recognition for motion prediction for example, and data compression.
Such vector comparison requires a massive amount of operations in any application. Further, von Neumann type computers, representative of which are PCs, cannot extract the most proximate vector until all vector comparison operations have been completed because of their operating principle and, as a result, extraction of the most proximate vector requires a very long time.
A conventional device (hereinafter will be referred to as “second conventional art”) based on a new concept for computing the “proximity” between plural numeric values (between a set of numeric values and another set of numeric values) at higher speed is described in, for example, “A CMOS Stochastic Associative Processor Using PWM Chaotic Signals”, IEICE Transactions on Electronics, Vol. E84-C, No. 12, December 200, pp. 1723-1729.
FIG. 34 illustrates the configuration of a distance processing apparatus according to the second conventional art.
The distance processing apparatus shown in FIG. 34 is an apparatus for stochastically processing the match/mismatch between digital data. When input data 101 matches with stored data 103 (both of the two are 1 or 0), XNOR circuit 120 outputs 1. To the output side of the XNOR circuit 120 is connected PWR chaos generator 121 for varying the pulse width chaotically. When latch signal 105 is inputted to latch circuit 122 after a certain time period after PWAM chaos has been generated, the value inputted at that time is held. Since the signal having a chaotically variable width is inputted to the latch circuit 122, an operation by which the value held by the latch circuit 122 becomes High is a stochastic operation. When High is held, switch 109 is turned ON to feed current from current source 107. By detecting the total sum of such currents and then performing comparison by high-order value extraction circuit 111, the sum of currents detected becomes stochastically larger as a group of input data 101 and a group of stored data 103 become more proximate to each other. Thus, the proximity between vectors (a humming distance in this case) can be calculated stochastically. Note that the second conventional art uses so-called logistic chaos as shown in the map of FIG. 35.
However, the distance processing apparatus of the second conventional art can only perform comparison between two values since the apparatus compares digital information. This means that the apparatus, as it is, operates only as a humming distance processing apparatus. Therefore, in comparing multiple-bit information the apparatus needs to perform comparisons between two values a number of times corresponding to the number of bits. This is not efficient.
Further, because the comparison of binary information (i.e., distance processing) is completed by XNOR, the introduction of chaos thereafter to obtain a chaotic solution is disadvantageous in terms of energy efficiency. Thus, the distance processing apparatus which processes digital information only cannot be expected to operate at reduced energy consumption.